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set.seed(602957) x <- rnorm(1000) noise <- rnorm(1000, sd=1.5) y <- 3*sin(2*x) + cos(0.75*x) - 1.5*(x^2 ) + noise select <- runif(1000) frame <- data.frame(y=y, x = x) train <- frame[select > 0.1,] test <-frame[select <= 0.1,] library(mgcv) glin.model <- gam(y~s(x), data=train) summary(glin.model) sx <- predict(glin.model, type="terms") xframe <- cbind(train, sx=sx[,1]) ggplot(xframe, aes(x=x)) + geom_point(aes(y=y), alpha=0.4) + geom_line(aes(y=sx)) 覿襯
library("mgcv") model <- gam(危覿 ~ s(覲1) + s(覲2),family=binomial, data=training) summary(model) pred <- predict(model, test, type="response") confusionMatrix(ifelse(pred < 0.5, "危", "譟"), test$危覿)
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譴 蟆 讌蠍 覦朱 螳螻 り 覩遂 蟆企. (一企 觜れ洲) |